MicroRNAs are important
negative regulators of protein-coding gene
expression and have been studied intensively over the past years.
Several measurement platforms have been developed to determine relative
miRNA abundance in biological samples using different technologies such
as small RNA sequencing, reverse transcription-quantitative PCR
(RT-qPCR) and (microarray) hybridization. In this study, we
systematically compared 12 commercially available platforms for
analysis of microRNA expression. We measured an identical set of 20
standardized positive and negative control samples, including human
universal reference RNA, human brain RNA and titrations thereof, human
serum samples and synthetic spikes from microRNA family members with
varying homology. We developed robust quality metrics to objectively
assess platform performance in terms of reproducibility, sensitivity,
accuracy, specificity and concordance of differential expression. The
results indicate that each method has its strengths and weaknesses,
which help to guide informed selection of a quantitative microRNA gene
expression platform for particular study goals.

MicroRNAs are small
non-coding RNAs that post-transcriptionally
regulate gene expression and their expression is frequently altered in
human diseases, including cancer. To correlate clinically relevant
parameters with microRNA expression, total RNA is frequently prepared
from samples that were archived for various time periods in frozen
tissue banks but, unfortunately, RNA integrity is not always preserved
in these frozen tissues. Here, we investigate whether experimentally
induced RNA degradation affects microRNA expression profiles. Tissue
samples were maintained on ice for defined time periods prior to total
RNA extraction, which resulted in different degrees of RNA degradation.
MicroRNA expression was then analyzed by microarray analysis (miCHIP)
or microRNA-specific real-time quantitative PCR (miQPCR). Our results
demonstrate that the loss of RNA integrity leads to in unpredictability
of microRNA expression profiles for both, array-based and miQPCR
assays. MicroRNA expression cannot be reliably profiled in degraded
total RNA. For the profiling of microRNAs we recommend use of RNA
samples with a RNA integrity number equal to or above seven.

The importance of high
quality sample material, i.e. non-degraded or
fragmented RNA, for classical gene expression profiling is well
documented. Hence, the analysis of RNA quality is a valuable tool in
the preparation of methods like RT-qPCR and microarray analysis. For
verification of RNA integrity, today the use of automated capillary
electrophoresis is state of the art. Following the recently published
MIQE guidelines, these pre-PCR evaluations have to be clearly
documented in scientific publication to increase experimental
transparency. RNA quality control may also be integrated in the routine
analysis of new applications like the investigation of microRNA (miRNA)
expression, as there is little known yet about factors compromising the
miRNA analysis. Agilent Technologies is offering a new lab-on-chip
application for the 2100 Bioanalyzer making it possible to quantify
miRNA in absolute amounts [pg] and as a percentage of small RNA [%].
Recent results showed that this analysis method is strongly influenced
by total RNA integrity. Ongoing RNA degradation is accompanied by the
formation of small RNA fragments leading to an overestimation of miRNA
amount on the chip. Total RNA integrity is known to affect the
performance of RT-qPCR as well as the quantitative results in mRNA
expression profiling. The actual study identified a comparable effect
for miRNA gene expression profiling. Using a suitable normalization
method could partly reduce the impairing effect of total RNA integrity.A comparison of miRNA isolation and RT-qPCR
technologies and their effects on quantification accuracy and
repeatability.
Redshaw N, Wilkes T, Whale A, Cowen S, Huggett J, Foy CA.
LGC Limited, Queens Road, Teddington, Middlesex, UK.
Biotechniques. 2013 54(3): 155-164

MicroRNAs (miRNAs) are short (~22 nucleotides), non-coding RNA
molecules that post-transcriptionally regulate gene expression. As the
miRNA field is still in its relative infancy, there is currently a lack
of consensus regarding optimal methodologies for miRNA quantification,
data analysis and data standardization. To investigate miRNA
measurement we selected a panel of both synthetic miRNA spikes and
endogenous miRNAs to evaluate assay performance, copy number
estimation, and relative quantification. We compared two different
miRNA quantification methodologies and also assessed the impact of
short RNA enrichment on the miRNA measurement. We found that both short
RNA enrichment and quantification strategy used had a significant
impact on miRNA measurement. Our findings illustrate that miRNA
quantification can be influenced by the choice of methodology and this
must be considered when interpreting miRNA analyses. Furthermore, we
show that synthetic miRNA spikes can be used as effective experimental
controls for the short RNA enrichment procedure.Validation
of extraction methods for total RNA and miRNA from bovine blood prior
to quantitative gene expression analyses.
Hammerle-Fickinger A, Riedmaier I, Becker C, Meyer HH, Pfaffl MW,
Ulbrich SE.
Biotechnol Lett. 2010 32(1): 35-44 Supplement -
Biotechnol Lett. 2010 32(1): 35-44Physiology Weihenstephan, Technische Universitaet
Muenchen, Weihenstephaner Berg 3, 85354, Freising, Germany.

The benefit and precision of blood diagnosis by quantitative real-time
PCR (qPCR) is limited by sampling procedures and RNA extraction
methods. We have compared five different RNA extraction protocols from
bovine blood regarding RNA and miRNA yield, quality, and most
reproducible data in the qRT-PCR with the lowest point of
quantification. Convincing results in terms of highest quantity,
quality, and best performance for mRNA qPCR were obtained by leukocyte
extraction following blood lysis as well as extraction of PAXgene
stabilized blood. The best microRNA qPCR results were obtained for
samples extracted by the leukocyte extraction method.

It is generally known
that total RNA quality has a distinct
influence on the validity and reliability of quantitative PCR results.
In addition, the recently published MIQE guidelines focus on the
pre-PCR steps and state the importance of RNA quality assessment.
Various studies showed the impairing effect of ongoing RNA degradation
on mRNA expression results. Therefore, the verification of RNA
integrity prior to downstream applications like RT-qPCR and
mircroarrays is indispensable. A fast and reliable assessment of RNA
integrity can be done with the Eukaryote Total RNA Nano Assay of the
Agilent 2100 Bioanalyzer. The importance of RNA quality should also be
considered in new applications such as the investigation of miRNA
expression profiles. With the Agilent Small RNA Assay, Agilent is
offering one of the few possibilities for selectively estimating miRNA
before expression analysis. However, by now little is known about
factors affecting miRNA analysis. Herein, the important impact of total
RNA quality on quantification of mRNA and miRNA should be considered.

MicroRNAs are
small, non–coding RNAs found in plants and animals. They regulate gene
expression by binding to complementary sequences within target mRNAs.
The mammalian genome encodes hundreds of miRNAs that collectively
affect the expression of about one–third of all genes. This collection
showcases the latest papers from Nature that explore the biogenesis,
biological effects in both normal and diseased cells, and therapeutic
potential of miRNAs.

microRNAs (miRNAs)
were initially considered a biological sideshow, the oddly interesting
regulators of developmental timing genes in Caenorhabditis elegans. But
in the past few years, studies have shown that miRNAs are a
considerable part of the transcriptional output of the genomes of
plants and animals, that they regulate a large part of their
transcriptomes and that they serve important regulatory functions in
widespread biological activities. Accordingly, miRNAs are now
recognized as an additional layer of post-transcriptional control that
must be accounted for if we are to understand the complexity of gene
expression and the regulatory potential of the genome. Owing to this
impressive progress in understanding the genomics and functions of
miRNAs, we think this is an ideal time to examine the available
evidence to see where this rapidly growing field is going.

In this
Supplement, we have focused on approaches to detect the
presence of miRNAs and their impact on genomes, and we explore the
roles they play in regulating biological functions. The Supplement
consists of five exploratory Perspectives and a comprehensive Review;
the pieces generally follow a progressive logic from discovery to
target prediction to function to systems perspective and finally to
organismal perspective.

Plant and animal
genomes have been shaped by miRNAs, as seen by the
substantial number of conserved miRNAs that have accumulated through
selection and the presence of miRNA target sites in genes of diverse
functions. However, the true number of miRNAs and targets remains
difficult to estimate. The detection of miRNAs is addressed in a
Perspective from Eugene Berezikov, Edwin Cuppen and Ronald Plasterk (p
S2), who discuss methods, both experimental and bioinformatic, for
discovering new miRNAs. These authors wrangle with the question of how
we define a 'true' miRNA and the implications this definition will have
for future studies. Approaches to the prediction of targets of miRNAs
are addressed by Nikolaus Rajewsky (p S8), who considers the case for
combinatorial control of target expression by multiple miRNAs acting
synergistically.

Some of the
fundamental goals of investigations into genome function
are to understand how the genome gives rise to different cell types,
how it contributes to basic and specialized functions in those cells
and how it contributes to the ways cells interact with the environment.
The roles of miRNAs in each of those functions are touched on in three
Perspectives. Jan Krützfeldt, Matthew Poy and Markus Stoffel (p
S14)
discuss approaches and technological advances useful to the
investigator studying miRNA function. Eran Hornstein and Noam Shomron
(p S20) take a systems approach to conceptualize a network of
interacting miRNAs and targets and propose that miRNAs act to canalize
developmental gene expression programs. And Bryan Cullen (p S25)
discusses recent evidence for pathogenic roles of virally encoded
miRNAs and proposes that cellular miRNAs influence the cell-type
specificity of invading viruses.

In the last piece,
Allison Mallory and Hervé Vaucheret (p S31) offer a
view of the diverse biological roles of miRNAs from an organismal
perspective in their Review of miRNAs and other endogenous regulatory
RNAs in plants. This piece highlights the contributions of regulatory
RNAs to developmental programs and stress responses.

Our hope is that
you find strategic advice and insight in this
Supplement. We invite you to access its contents online at
http://www.nature.com/ng/supplements/, where it will be freely
available for 3 months. In addition to the pieces featured here, online
we provide links to related articles on miRNAs published by the Nature
Publishing Group and an animation entitled 'Lifecycle of an miRNA'
supplied by Rosetta Genomics.

We are grateful to
our authors for their insightful contributions, as
well as to our referees for their valuable comments during the review
process. In addition, we gratefully acknowledge the support of our
principal sponsors, Rosetta Genomics and Alnylam Pharmaceuticals, and
our supporting sponsor, Santaris Pharma, for their help in producing
this Supplement and making it freely available online.

Nature Reviews
presents a Collection on microRNAs, which includes Reviews from Nature
Reviews Genetics, Nature Reviews Cancer and Nature Reviews Molecular
Cell Biology. The articles have been specially selected to provide an
introduction to diverse aspects of microRNA biology, including their
biogenesis, function in normal development and cancer, and evolutionary
implications of their impact on gene regulation.

In 1993, R.C. Lee of
Harvard University first described miRNA-mediated silencing in C.
elegans, and since, these molecules have been more clearly defined as
single-stranded RNA molecules, 19-25 nucleotides in length, that are
generated from endogenous hairpin transcripts. MicroRNAs (miRNAs) serve
as guides in post-transcriptional gene silencing by complimentary base
pairing with target mRNAs, resulting in mRNA cleavage or translational
repression. As a result, miRNAs enable regulation of complex biological
pathways such as those associated with developmental processes,
haematopoietic cell differentiation, apoptosis, and cell proliferation.
Interestingly, it now appears that miRNAs may actually form complex
regulatory networks with target mRNAs, as a single miRNA may be
responsible for the regulation of several different targets, or
conversly, several miRNAs may cooperatively regulate a single mRNA
target. To date, there have been approximately 4300 precursor miRNAs
found in virtually all species—animals, plants, and viruses—of which
~475 are human miRNAs. Research suggests that as many as one-third of
all human genes may be miRNA regulated, many of which are involved in
cancer and other disease regulation.

Due to their involvement
in gene regulation, miRNAs have received significant attention with
respect to their role in cancer, disease, and stem cell
differentiation. Traditional characterization of miRNA follows small
RNA identification by cDNA cloning. Expression of miRNAs is typically
confirmed by hybridization to a size-fractionated RNA sample, usually
achieved by Nothern blot analysis. Alternative methods for miRNA
detection and confirmation include reverse transcription PCR (RT-PCR),
primer extension analysis, RNase protection assays, and microarray
analysis. Typically, even when miRNAs are identified using these
alternative methods, Northern blot analysis follows as it enables the
confirmation of both the hairpin precursor (~70 nt) and mature miRNA
(~22 nt) forms. Global gene expression profiling of miRNAs using
microarrays provides high-throughput information on miRNA involvement
in disease progression and developmental changes, while offering an
alternative to some of the time- and labor-intensive techniques
previously described.

Although
they are tiny, microRNAs can have large-scale effects because they
regulate a variety of genes. These minuscule molecules are now
definitively linked to the development of cancer. During the past few
years, molecular biologists have been stunned by
the discovery of hundreds of genes that encode small RNA molecules.
These microRNAs (miRNAs -21 to 25 nucleotides in length)- are
negative regulators of gene expression. The mechanisms by which they
work are similar in plants and animals, implying that they are involved
in fundamental cellular processes.
As cancer is essentially a consequence of disordered genome function,
one might expect these regulatory molecules to be involved in the
development of this disease. Indeed, there are hints that the levels of
some miRNAs are altered in cancer; there is also evidence that an miRNA
regulates the cancer-promoting ras gene.
Three studies in this issue
change the landscape of cancer genetics by establishing the specific
miRNAs expressed in most common cancers, and investigating the effects
of miRNAs on cancer development and cancer genes..............

The
precursor of an miRNA (pri-miRNA) is transcribed in the nucleus. It
forms a stem−loop structure that is processed to form another precursor
(pre-miRNA) before being exported to the cytoplasm. Further processing
by the Dicer protein creates the mature miRNA, one strand of which is
incorporated into the RNA-induced silencing complex (RISC). Base
pairing between the miRNA and its target directs RISC to either destroy
the mRNA or impede its translation into protein. The initial stem−loop
configuration of the primary transcript provides structural clues that
have been used to guide searches of genomic sequence for candidate
miRNA genes.

MicroRNAs
are regulatory, non-coding RNAs about 22 nucleotides in length: over
200 have been identified in humans, and their functions are beginning
to be pinned down. It has been suggested that like other regulatory
molecules they might be involved in tumour formation, and three papers
in this issue confirm that this is the case. One cluster of microRNAs,
known as mir-17−92, is shown to be a potential oncogene by its
action in an in vivo
model of human B-cell lymphoma. A cluster of microRNAs on human
chromosome 13 has been found to be regulated by c-Myc, an important
transcription factor that is overexpressed in many human cancers. And
analysis of microRNA expression in over 300 individuals shows that
microRNA profiles could be of value in cancer diagnosis. There is a
global downregulation of microRNA in tumours, and the microRNA profile
also reflects the origin and differentiation state of the tumours.Letter: A microRNA
polycistron as a
potential human oncogeneLin He, J. Michael Thomson, Michael T. Hemann, Eva
Hernando-Monge,
David Mu, Summer Goodson, Scott Powers, Carlos Cordon-Cardo, Scott W.
Lowe, Gregory J. Hannon and Scott M. HammondLetter:
MicroRNA expression
profiles classify human cancersJun Lu, Gad Getz, Eric A. Miska, Ezequiel
Alvarez-Saavedra, Justin
Lamb, David Peck, Alejandro Sweet-Cordero, Benjamin L. Ebert, Raymond
H. Mak, Adolfo A. Ferrando, James R. Downing, Tyler Jacks, H. Robert
Horvitz and Todd R. GolubLetter:
c-Myc-regulated
microRNAs modulate E2F1 expressionKathryn A. O'Donnell, Erik A. Wentzel, Karen I. Zeller,
Chi V. Dang and
Joshua T. Mendell

Sizing up
miRNAs as cancer genes

Carlos Caldas & James D Brenton

The
authors are in the Cancer Genomics Program, Department of Oncology,
University of Cambridge and Cambridge University Hospitals National
Health Service Foundation Trust, Cambridge CB2 2XZ, UK. Findings over the last year or so have built the case that
microRNAs
might contribute to cancer. Three studies now definitively show this to
be the case and also suggest that these small RNAs could be used to
categorize tumors.

microRNAs (miRNAs)
are a new class of non-protein-coding, endogenous, small RNAs. They are
important regulatory molecules in animals and plants.
miRNA
regulates gene expression by translational repression, mRNA cleavage,
and mRNA decay initiated by miRNA-guided rapid deadenylation.
Recent
studies show that some miRNAs regulate cell proliferation and apoptosis
processes that are important in cancer formation. By
using multiple
molecular techniques, which include Northern blot analysis, real-time
PCR, miRNA microarray, up- or down-expression of specific
miRNAs, it
was found that several miRNAs were directly involved in human cancers,
including lung, breast, brain, liver, colon cancer, and
leukemia. In
addition, some miRNAs may function as oncogenes or tumor suppressors.
More than 50% of miRNA genes are located in cancer-associated
genomic regions or in fragile sites, suggesting that miRNAs may play a
more important role in the pathogenesis of a limited range
of human
cancers than previously thought. Overexpressed miRNAs in cancers, such
as mir-17–92, may function as oncogenes and promote cancer
development by
negatively regulating tumor suppressor genes and/or genes that control
cell differentiation or apoptosis. Underexpressed miRNAs
in cancers,
such as let-7, function as tumor suppressor genes and may inhibit
cancers by regulating oncogenes and/or genes that control cell
differentiation
or apoptosis. miRNA expression profiles may become useful biomarkers
for cancer diagnostics. In addition, miRNA therapy could
be a powerful
tool for cancer prevention and therapeutics.

MicroRNAs
(miRNAs) play
important roles in gene expression regulation in animals and
plants. Since plant miRNAs recognize their target mRNAs by near-perfect
base pairing, computational sequence similarity search
can be used to identify potential targets. A web-based
integrated computing system, miRU, has been developed
for plant miRNA target gene prediction in any plant, if a large number of
sequences are available. Given a mature miRNA sequence from a plant
species, the system thoroughly searches for potential
complementary target sites with mismatches tolerable in
miRNA-target recognition. True or false positives are estimated
based on the number and type of mismatches in the target site, and on the
evolutionary conservation of target complementarity in another genome
which can be selected according to miRNA conservation.
The output for predicted targets, ordered by mismatch
scores, includes complementary sequences with mismatches
highlighted in colors, original gene sequences and associated functional
annotations.
The miRU web server is available at http://bioinfo3.noble.org/miRU.htm

The RNAi Consortium, or
TRC, is a public-private effort
based at the Broad whose mission is to create a shRNA library as well
to validate tools and methods that will enable the scientific community
to use RNAi to determine the function of human and mouse genes. The
reagents are composed of short hairpin sequences carried in lentiviral
vectors arrayed in 96-well plates.

The RNAi Consortium - * Details on the TRC
shRNA Library

Since RNA interference (RNAi) was discovered to work in
mammalian
cells, the genetic manipulation technique has been hailed as a
revolutionary new approach to basic biological research and drug
development and discovery. RNAi is expected to provide critical
insights into the mechanisms underlying human disease and accelerating
development of treatments for cancer, AIDS and a host of other
disorders.A public-private consortium based at the Broad will
develop and
validate tools and methods that will enable the worldwide scientific
community to use RNAi to unveil the function of most human and mouse
genes. The goal of the RNAi Consortium (abbreviated TRC) is to use the
recently discovered RNAi mechanism to create widely applicable research
reagents consisting of specific inhibitors against human and mouse
genes. The reagents are composed of short hairpin sequences carried in
lentiviral vectors. They can be used in a wide range of cellular and
animal studies to discover the key genes underlying normal physiology
and disease.In a three-year, $18 million initiative, the TRC will
create a library
of materials to conduct RNAi experiments on 15,000 human genes and
15,000 mouse genes. A total of 150,000 custom-designed plasmids that
express short and unique pieces of RNA (known as short hairpin RNAs or
shRNAs) that target specific genes will be created and validated. This
fundamental resource will be made available to scientists worldwide
through commercial and academic distributors.In addition to the Broad, TRC partners include Harvard
Medical School
(HMS), the Massachusetts Institute of Technology (MIT), Dana-Farber
Cancer Institute (DFCI), the Whitehead Institute for Biomedical
Research (WIBR), Novartis, Eli Lilly, Bristol-Myers Squibb,
Sigma-Aldrich and research institute Academia Sinica in Taiwan.The Principal Investigators of TRC are Dr. Nir Hacohen
(Broad Associate
Member; Massachusetts General Hospital, HMS), Dr. William Hahn (Broad
Associate Member; DFCI, HMS), Dr. Eric Lander (Broad Institute), Dr.
David Root (TRC Project Manager, Broad Institute), Dr. David Sabatini
(Broad Associate Member; WIBR, MIT), Dr. Sheila Stewart (Washington
University, formerly at WIBR), and Dr. Brent Stockwell (Columbia
University, formerly at WIBR).

The
abbreviated name, ‘mfold web server’, describes a number of closely
related software applications available on the World Wide Web (WWW) for
the prediction of the secondary structure of single stranded nucleic
acids. The objective of this web server is to provide easy access to
RNA and DNA folding and hybridization software to the scientific
community at large. By making use of universally available web GUIs
(Graphical User Interfaces), the server circumvents the problem of
portability of this software. Detailed output, in the form of structure
plots with or without reliability information, single strand frequency
plots and ‘energy dot plots’, are available for the folding of single
sequences. A variety of ‘bulk’ servers give less information, but in a
shorter time and for up to hundreds of sequences at once. The portal
for the mfold web server is http://www.bioinfo.rpi.edu/applications/mfold
This URL will be referred to as ‘MFOLDROOT’.

An improved dynamic programming algorithm is reported for RNA secondary
structure prediction by free energy minimization. Thermodynamic
parameters for the stabilities of secondary structure motifs are
revised to include expanded sequence dependence as revealed by recent
experiments. Additional algorithmic improvements include reduced search
time and storage for multibranch loop free energies and improved
imposition of folding constraints. An extended database of 151,503 nt
in 955 structures? determined by comparative sequence analysis was
assembled to allow optimization of parameters not based on experiments
and to test the accuracy of the algorithm. On average, the predicted
lowest free energy structure contains 73 % of known base-pairs when
domains of fewer than 700 nt are folded; this compares with 64 %
accuracy for previous versions of the algorithm and parameters. For a
given sequence, a set of 750 generated structures contains one
structure that, on average, has 86 % of known base-pairs. Experimental
constraints, derived from enzymatic and flavin mononucleotide cleavage,
improve the accuracy of structure predictions.

miRBase
- the home of microRNA data

miRBase http://microrna.sanger.ac.uk/ is the new home of microRNA
data on the web, providing data previously
accessible from the miRNA Registry. Old miRNA Registry addresses
should redirect you to this page.

The miRBase
Sequence
Database is a
searchable database of published miRNA sequences and annotation. The
data were previously provided by the miRNA Registry.The miRBase
Registry continues to provide
gene hunters with unique names for novel miRNA genes prior to
publication of results.The miRBase
Targets database is a new
resource of predicted miRNA targets in animals.

Each entry in the miRBase
Sequence database represents a predicted
hairpin portion of a miRNA transcript (termed mir in the database),
with information on the location and sequence of the mature miRNA
sequence (termed miR). Both hairpin and mature sequences are
available for searching
using BLAST and
SSEARCH, and entries can also be retrieved by name, keyword,
references and annotation. All sequence and annotation data are also available
for download.

Please
note that the predicted stem-loop
sequences in the database are not strictly precursor miRNAs
(pre-miRNAs), but include the pre-miRNA and some flanking sequence
from the presumed primary transcript.

Please use the tabs along
the top of this page to access the
different areas of the site, or you can click here
to jump to the help pages. A summary of the data available in the
current release is provided here.

To receive email
notification of data updates and feature changes
please subscribe to the microRNA
mailing
list. Any other queries about the website or naming service
should be directed at microRNA@sanger.ac.uk.

References:
If you make use of
the data presented here,
please cite the following articles in addition to the primary data
sources

The miRNA Registry
provides a service for the assignment of miRNA gene names prior to
publication. A comprehensive and searchable database of published miRNA
sequences is accessible via a web interface (http://www.sanger.ac.uk/Software/Rfam/mirna/),
and all sequence and annotation data are freely available for download.
Release 2.0 of the database contains 506 miRNA entries from six
organisms.

MicroRNAs (miRNAs) are
small noncoding RNA gene products about 22 nt long that are processed
by Dicer from precursors with a characteristic hairpin secondary
structure. Guidelines are presented for the identification and
annotation of new miRNAsfrom diverse organisms,
particularly so that miRNAs can be reliably distinguished from other
RNAs such as small interfering RNAs. We describe specific criteria for
the experimental verification of miRNAs, and conventions for naming
miRNAs and miRNA genes. Finally, an online clearinghouse for miRNA gene
name assignments is provided by the Rfam database of RNA families.